Integrated actuators – Prof. Y. Perriard
Note: Projects are intended for Microengineering, Electrical Engineering, Computer Science and Mechanical Engineering sections.
For information and registrations contact:
- Prof. Yves Perriard at: [email protected]
- Paolo Germano at: [email protected]
Transportation fees between EPFL and Neuchâtel will be covered.
- Project # 1 – Self-Sensing for dielectric elastomer actuators
- Simon Holzer
Dielectric Elastomer Actuators (DEAs) are deformable materials frequently employed in soft robotics, distinguished by high energy density. Often referred to artificial muscles, they deform based on the electrostatic principle, where the application of high voltage induces thickness reduction which will lead to an increase of surface in the other directions.
This project aims to apply self-sensing in soft robotics to ascertain the state of the DEAs. Self-sensing is defined as sensing the state of the actuator during actuation without the use of additional sensors (also called sensor-less sensing). The project includes studies on the state of the art, implementing the code (LabView/Python or others) for the chosen method and test the functionality by experiments. The experiments will include tests with changing stiffness which should be determined. The stiffness will be adapted by example by affixing various rigid materials, potentially of biological origin, to the surface and determine these changes in rigidity.
The following tasks will be done during your project:
– Performing a state of the art about existing self-sensing technologies
– Choice and implementation of a promising self-sensing method
– Experiments on existing DEA platforms to show abilities of the implemented method
– Writing project report
Keywords: Self-sensing, soft robotics, biomedical engineering
[1]: Kwangmok Jung, Kwang J. Kim, Hyouk Ryeol Choi (2008), A self-sensing dielectric elastomer actuator in Sensors and Actuators A: Physical, Volume 143, Issue 2, https://doi.org/10.1016/j.sna.2007.10.076.
. - Project # 2 – Transparent Electrodes for dielectric elastomer actuators
- Simon Holzer
Dielectric Elastomer Actuators (DEAs) represent a type of artificial muscle stimulated by high voltage. The applied high voltage generates a Maxwell pressure, resulting in DEA deformation. The electrodes of the DEA play a pivotal role, influencing the generated electric field through their shape, material and other properties. Frequently employed electrodes for DEAs, based on carbon or silver, are often opaque and do not permit light transmission [1].
This project focuses on developing DEAs with transparent stretchable electrodes. This involves determining the appropriate material, developing a subsequent process for transparent DEA fabrication, and conducting various tests on the electrodes to analyse their behaviour in comparison to traditionally used electrodes. The fabrication of the electrodes will be conducted in-house within a cleanroom and different technologies like blade casting, pad printing or inkjet printing are possible to be used. For you, this project provides an opportunity for initial experiences in a cleanroom environment and the possibility to work with state-of-the-art manufacturing processes utilized in the field of soft robotics.
The following tasks will be done during your project:
– Performing a literature review about existing stretchable transparent electrodes
– Development of a fabrication strategy for a transparent electrode on PDMS
– Testing of properties and functionality of developed transparent electrode
– Writing project report
Keywords: Transparent stretchable electrodes, Cleanroom, soft robotics
[1]: Rosset, S., Shea, H.R. (2013) Flexible and stretchable electrodes for dielectric elastomer actuators. In Appl. Phys. A 110, 281–307. https://doi.org/10.1007/s00339-012-7402-8
. - Project # 3 – Control and Implementation of a soft planar actuator for a precise assembly station
- Simon Holzer
In the recent years various micro assembly stations are developed which are used to address wide range of needs such as high precision, stroke, speed etc. Planar actuators based on soft actuators can provide several advantages including light weight, higher stroke and stress withstanding [1]. Through this study we aim to develop and advance the control scheme of the already developed planar soft actuator. The successful student would study and analyse the planar actuator, master the system handling by establishing an appropriate control to ensure precise trajectory generation.
The following tasks will be done during your project:
· Performing a state of the art about existing micro assembly stations and their limitations
· Establish an appropriate control of the device
· Experiments on existing DEA platforms to apply established control algorithm
· Writing project report
Keywords: Control strategies, soft robotics, signal processing
. - Project # 4 – Topology for piezoelectric motor optimization in frequency domain
- Marc Favier
Due to the advantages of compact structure, high energy density, fast response rate and high motion precision, piezoelectric motors (PMs) are widely employed in aerospace, optics, medical instruments. As a typical type of electromechanical coupling device, the structural optimization issue of PMs is undergoing significant.
Topology optimization is a mathematical method that optimizes material layout within a given design space, for a given set of loads, boundary conditions and constraints with the goal of maximizing the performance of the system, which is a good option for the initial design of PM structures, as it can greatly improve design flexibility and obtain some feasible but counterintuitive structures.
The goals of this project:
a) using commercial finite element analysis (FEM) to explore PM structures;
b) develop new algorithms for topology optimization improvement.
Applicants need to have the following skills:
a) a basic knowledge of mathematics, such as calculus and linear algebra;
b) a basic knowledge of physics, such as material mechanics and structural mechanics;
c) at least one programming language, such as python, MATLAB;
d) a good understanding of finite element analysis.
. - Project # 5 – Designing a Kirigami-Inspired SMA-Based Structure for Actuation
- Marjan Ghorbani
Shape memory alloys (SMAs) are popular as actuators for soft bioinspired robots because they are naturally compliant, have high work density, have a wide range of applications from aerospace to the medical industry, and can be operated using minimized onboard electronics for power and control. Shape memory alloys are interesting because of their unique characteristic which is remembering their initial shaped.
The objective of this semester project is to explore and design a Shape Memory Alloy (SMA)-based actuation structure inspired by Kirigami, integrating COMSOL Multiphysics simulation.
The project aims to leverage the unique properties of SMAs, coupled with Kirigami’s patterns, to create an innovative actuation system with improved behaviour compared to conventional designs.
To do so, the student will be asked to design and simulate different patterns in terms of mechanical and thermal behavior to generate the required force and actuate in the desired time. In another way, the proposed pattern should be optimized enough to deliver the requirements. The student will also have the opportunity to experience different aspects of SMAs which are one of the most applicable alloys in the different fields of the novel industry.
The proposed project comprises different steps:
1. Literature Review: Conduct an in-depth review of existing literature on Shape Memory Alloys, Kirigami structures, and COMSOL simulation. Understand the principles, challenges, and opportunities associated with combining these technologies.
2. Conceptual Design: Develop conceptual designs for the Kirigami-inspired SMA-based actuation structure, considering different cutting patterns.
3. COMSOL Multiphysics Simulation: Create a model of the Kirigami-inspired SMA structure using COMSOL Multiphysics. Simulate the mechanical and thermal behavior of the structure and correlate the simulation results with experimental findings.
4. Fabrication and Prototyping: Fabricate prototypes of the proposed Kirigami-inspired SMA structure. Utilize manufacturing techniques, such as laser cutting, for precision in Kirigami patterns.
5. Actuation Testing: Conduct experiments to evaluate the designed structure performance. Investigate factors such as response time, force generation, and repeatability. Adjust the design based on both experimental and simulation results.
6. Analysis and Optimization: Perform structural and thermal analyses using COMSOL to understand the behavior of the Kirigami-inspired SMA structure. Optimize the design based on the combined insights from experimental and simulated data.
7. Final Report and Presentation: Document the entire design process, including literature review, conceptual design, simulation, fabrication, testing, and analysis. Prepare a comprehensive report and deliver a presentation summarizing key findings and the significance of the designed structure.
Expected outcomes are:
1. A Kirigami-inspired SMA-based actuation structure with demonstrated capabilities.
2. Correlation between COMSOL simulation and experimental results.
3. Insights into the integration of Kirigami, SMAs, and COMSOL for innovative engineering applications.
4. Recommendations for further improvements and potential applications.
. - Project # 6 – Constant Force Actuator – Force profiles implementation
- Maël Dagon, Paolo Germano
In the frame of the development of a medical foot pressure releasing linear valve (Fig. 1), there is a need of mechanically loading the device with a constant force independently of the stroke. Commonly, weights of different sizes are used but are not really convenient (Fig. 2) especially when a specific force profile is needed. The aim of the project is to program a voice-coil based (or any suitable) loader to be able to easily dynamically characterize the developed valve.
Fig. 1
Fig. 2
. - Project # 7 – Development of Tubular Valves based on Soft Electrohydraulic Actuators for Biomedical Engineering Applications
- Purnendu
Introduction: Soft electrohydraulic actuators (SEA) offer promising opportunities in biomedical engineering due to their ability to mimic the compliance and functionality of biological tissues. This project aims to develop soft electrohydraulic actuators, focusing on the design and implementation of tubular valves for various biomedical applications.
Objective: The primary objective of this project is to design, fabricate, and validate tubular valves based on soft electrohydraulic actuators for biomedical engineering applications, focusing on artificial urinary sphincters and aortic augmentation devices.
Approach:
1. Valve Design:
– Design of a soft electrohydraulic actuator to be used as a valve.
– Simulation of the valve to mimic the function of natural sphincters and/or aortic valves, ensuring optimal fluid regulation.
– Utilize soft and biocompatible materials to construct the valve’s flexible structure.
2. Electrohydraulic Actuation:
– Integrate electrohydraulic actuation components within the valve’s structure.
– Develop control systems to regulate valve opening and closing.
3. Prototype Fabrication and Testing:
– Fabricate prototypes of the tubular valves based on the designed specifications.
– Conduct benchtop experiments to evaluate the valve’s performance, including response time, sealing efficiency, and durability.
– Possibility to validate the functionality of the artificial urinary sphincter and aortic augmentation devices in simulated physiological conditions
Expected Outcomes:
– Design and development of tubular valves based on soft electrohydraulic actuators optimized for biomedical engineering applications.
– Creation of prototypes of the valves as well as demonstrating the feasibility of utilizing soft actuators for artificial urinary sphincters and aortic augmentation devices.
Conclusion:
This project aims to contribute to the advancement of biomedical engineering by developing tubular valves based on soft electrohydraulic actuators, with applications in artificial urinary sphincters and aortic augmentation devices. By leveraging innovative soft robotics technology, we aim to address critical healthcare needs and improve patient outcomes in urology and cardiovascular medicine.
Preferred Qualifications:
– The student should have a passion to design and develop novel hardware.
– The student should be interested in experimental lab work. Someone with good and meticulous hands will be preferred. Prior experience tinkering with hardware is preferable but not necessary. The student will be taught how to fabricate these actuators using a semi-automated fabrication set up.
General curiosity and openness to try and learn new things will be appreciated
. - Project # 8 – Machine Learning-based Modeling and Control of Soft Electrohydraulic Actuators
- Purnendu
Introduction: Soft electro-hydraulic actuators (SEA) have gained significant attention due to their potential in achieving complex and adaptable movements in robotics and industrial automation. However, their nonlinear behavior and compliance pose challenges in traditional control methods. This project proposes the use of machine learning techniques to model and control soft electrohydraulic actuators, aiming to improve their performance, efficiency, and adaptability.
Objective: The main objective of this project is to develop machine learning-based models and control strategies for soft electrohydraulic actuators to enhance their performance and adaptability in various applications.
Approaches: The student is encouraged to propose alternate algorithms or come up with their own. However, we can also use approaches like:
A. Reinforcement Learning (RL):
Reinforcement learning is a powerful paradigm for learning optimal control policies through interaction with the environment. In this approach, the SEA system will interact with the environment (simulated or real-world) to learn optimal control policies. The RL agent will receive feedback in the form of rewards based on its actions and will adjust its behavior to maximize long-term rewards. This approach has the advantage of adaptability and the ability to handle complex, nonlinear systems.
B. Long Short-Term Memory (LSTM) Deep Neural Network:
LSTM networks are capable of learning temporal dependencies in data, making them suitable for time-series prediction and control tasks. In this approach, LSTM-based models will be trained to predict the behavior of soft electrohydraulic actuators based on historical sensor data. The trained LSTM models can then be used for control, predicting future states of the system and generating control signals accordingly. This approach is advantageous for its ability to handle time-varying dynamics and learn complex patterns from data.
Methodology:
1. Data Collection and Preprocessing:
– Collect sensor data from soft electrohydraulic actuators.
– Preprocess the data to remove noise and outliers, and format it for training.
2. Model Training:
– Come up with a machine learning pipeline employing RL/LSTM or an entirely new approach.
– For RL: Implement an RL agent using algorithms like Deep Q-Networks (DQN) or Proximal Policy Optimization (PPO).
– For LSTM: Train LSTM-based models on the preprocessed data to learn the system dynamics.
3. Control Strategy Development:
– Develop control strategies based on the trained models for the algorithms.
– Implement control algorithms for real-time control of soft electrohydraulic actuators.
4. Evaluation:
– Evaluate the performance of RL and LSTM-based control strategies in terms of accuracy, stability, and efficiency.
– Compare the proposed approaches with traditional control methods .
Expected Outcomes:
– Development of desired machine learning-based models for soft electrohydraulic actuators.
– Implementation of efficient control strategies for improved performance and adaptability.
– Demonstration of the feasibility and effectiveness of machine learning in enhancing the control of soft electrohydraulic actuators.
Conclusion: This project proposes the use of machine learning techniques, (like reinforcement learning and LSTM-based neural networks), for modeling and controlling soft electrohydraulic actuators. By leveraging these approaches, we aim to overcome the limitations of traditional control methods and improve the performance and adaptability of soft actuators in various applications.
Preferred Qualifications:
– The student should have deep interest in machine learning and/or actuators and sensors.
– Understanding of the foundations of machine learning models will be great. Prior experience training RL/LSTM or similar algorithms is preferable but not necessary. General curiosity and openness to try and learn new things will be appreciated.
. - Project # 9 – Simulation and Topology Optimization of Fiber Actuators for Bioinspired Robotics and Biomedical Engineering Applications
- Purnendu
Introduction: Fiber actuators, which involve thin high voltage wires subjected to high AC voltages, offer a promising avenue for creating soft and flexible actuators suitable for various applications. This project aims to simulate and optimize the topology of patterns based on these fiber actuators to enhance their performance and versatility. The applications of these actuators span across bioinspired robotics and biomedical engineering, offering innovative solutions for soft robotics and medical devices.
Objective: The primary objective of this project is to simulate and optimize the topology of patterns in fiber actuators to improve their efficiency, flexibility, and reliability.
Approach:
– Employ topology optimization algorithms to design and optimize the patterns of fiber actuators.
– Use finite element analysis (FEA) to analyze stress distribution, deformation, and resonance behavior of the patterns.
– Define optimization objectives, such as maximizing actuation displacement, minimizing energy consumption, or enhancing robustness.
– Perform iterative optimization to refine the actuator patterns based on simulation results.
Come up with application scenarios based on the results.
Expected Outcomes:
– Simulation models provide insights into the behavior of fiber actuators under different operating conditions.
– Optimized patterns for fiber actuators, enhancing their performance and versatility.
– Simple demonstration of these actuators for an application spanning bio-inspired robotics or biomedical engineering.
Conclusion: This project proposes the simulation and topology optimization of fiber actuators, driven by high AC voltages, for applications in bioinspired robotics and biomedical engineering. By leveraging computational modeling and optimization techniques, we aim to enhance the capabilities of these actuators, making them more efficient, flexible, and reliable. The outcomes of this project will contribute to the development of innovative soft actuators with applications in fields ranging from bioinspired robotics to medical devices.
Preferred Qualifications:
– The student should have interest in actuators and sensors.
– Prior experience with FEA simulations is preferable but not necessary. Simulations will be made in COMSOL or a similar platform (if the student prefers) which are easy to learn. General curiosity and openness to try and learn new things will be appreciated.
. - Project # 10 – Multiaxial sensing insole design
- Maël Dagon, Paolo Germano, Andrés Osorio
Multi-axial sensing insole for person with diabetes
Every 20 seconds, someone with diabetes is subjected to amputation somewhere in the world. The primary risk factor for these amputations is the high normal and shear plantar pressure (PP), coupled with a lack of sensation in the feet. The plantar pressure distribution changes throughout the day according to various uncontrollable factors, such as activity, walking surface type, posture adjustments, etc. Therefore, an intelligent offloading system that can autonomously and continuously redistribute local PPs is highly desirable.
In our laboratory, we have successfully developed an intelligent offloading shoe, which operates on the principle of discretization of the sole area and integration of magnetorheological fluid (MRF) modules for actuation [1]. We use a piezoresistive material to provide PP feedback to the controller in the normal direction, allowing the system to determine the appropriate offloading approach in real time [2].
With the aim of including both normal and shear PP sensing capabilities, which would improve the offloading capabilities of our intelligent offloading shoe, we propose a project for the development of a new multi-axis PP sensing insole, which will make use of smart elastomer sensors. The sensing range of this sensor should be > 200 kPa and 1 MPa, respectively, for shear and normal PP corresponding to a sensing area < 100 mm2, so that it can be integrated with our offloading system.
The following tasks will be done during the project:
– Evaluation of state of the art of elastomer sensors and their manufacture;
– Selection of manufacturing and design of novel elastomer-based sensing insole;
– Manufacture, validation and characterization of a sensing insole prototype capable of normal and shear plantar pressure.
With your participation in this project, you would not only advance the technology available for patients suffering from diabetes, but you would also gain knowledge in:
– Advanced sensor technology and materials science;
– The design and integration of smart systems for medical applications;
– Development and testing of innovative healthcare solutions.
References:
[1] Hemler, S. L., Ntella, S. L., Jeanmonod, K., Köchli, C., Tiwari, B., Civet, Y., Pataky, Z. (2023). Intelligent plantar pressure offloading for the prevention of diabetic foot ulcers and amputations. Frontiers in Endocrinology, 14, 1166513.
[2] Tiwari, B., Ntella, S. L., Jeanmonod, K., Germano, P., Koechli, C., Pataky, Z., Perriard, Y. (2023). A Polyester-Nylon Blend Plantar Pressure Sensing Insole for Person with Diabetes. IEEE Sensors Letters.
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- Project # 11 – Signals synchronization
- Maël Dagon, Paolo Germano, Andrés Osorio
Diabetic foot ulcers are a major problem that are commonly caused by high pressures under the foot (plantar pressure – PP). Our team is developing intelligent footwear that can sense where there are high plantar pressures and then automatically adapt the contour of the insole to redistribute the pressures. To test the feasibility of this footwear, bio-mechanical measurements will be performed in a gait lab at the Geneva University Hospitals (HUG). A motion capture system will track the movement of the patients, EMGs will track the muscle activity, and two pressure sensing systems – a gold-standard pressure sensing system (PEDAR®) and our own pressure sensing insoles – will track the plantar pressures. For accurate analysis, it is of main importance that these 4 related measurements are synchronized.
The goal of this project is to implement mathematical tools that synchronizes these four sets of data.
Applicants need to have the following skills:
a) Basic knowledge of data acquisition and data analysis;
b) Programming language, such as python or MATLAB, …
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